scholarly journals Drought analysis over northern Thailand

2021 ◽  
Vol 2145 (1) ◽  
pp. 012047
Author(s):  
Pakpoom Ratjiranukool ◽  
Sujittra Ratjiranukool
Keyword(s):  
Kalman Filter ◽  
Regional Climate Model ◽  
Rainy Season ◽  
Climate Model ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Filter Method ◽  
Northern Thailand ◽  
Drought Conditions ◽  
Kalman Filter Method

Abstract In this research, the Kalman filter method was applied for correcting precipitations simulated by a high-resolution regional climate model named Non-hydrostatic Regional Climate Model (NHRCM) during the period of 1980-1999. The improved average monthly precipitations were close to the stational observations. To reduce systematic error, the Kalman filter method was also applied to simulated monthly precipitations during the future period of 2080-2099. They were analysed to evaluate drought conditions during March-April (out rainy season) and June-July (in rainy season) by using Standardized Precipitation Index, SPI. Preliminary Analysis shows that drought conditions during both periods slightly mitigate. Furthermore, the drought over upper northern Thailand was found in the wettest month during the southwest monsoon period, September. The other months during the monsoon active are wetter than the period of 1980-1999.

Evaluation of Temperature Simulation over Northern Thailand from Regional Climate Model Coupled with Land Surface Model

2017 ◽  
Vol 866 ◽  
pp. 108-111
Author(s):  
Theerapan Saesong ◽  
Pakpoom Ratjiranukool ◽  
Sujittra Ratjiranukool
Keyword(s):  
Regional Climate Model ◽  
Land Surface ◽  
Climate Model ◽  
Global Analysis ◽  
Regional Climate ◽  
Land Surface Model ◽  
Analysis Data ◽  
Surface Model ◽  
Northern Thailand ◽  
Weather Model

Numerical Weather Model called The Weather Research and Forecasting model, WRF, developed by National Center for Atmospheric Research (NCAR) is adapted to be regional climate model. The model is run to perform the daily mean air surface temperatures over northern Thailand in 2010. Boundery dataset provided by National Centers for Environmental Prediction, NCEP FNL, (Final) Operational Global Analysis data which are on 10 x 10. The simulated temperatures by WRF with four land surface options, i.e., no land surface scheme (option 0), thermal diffusion (option 1), Noah land-surface (option 2) and RUC land-surface (option 3) were compared against observational data from Thai Meteorological Department (TMD). Preliminary analysis indicated WRF simulations with Noah scheme were able to reproduce the most reliable daily mean temperatures over northern Thailand.

scholarly journals Pengaruh koreksi bias dan metode ensemble pada data curah hujan dari empat model luaran Regional Climate Model (RCM) CORDEX-SEA di Sumatera

2021 ◽  
Vol 11 (1) ◽  
pp. 49-56
Author(s):  
Irza Arnita Nur ◽  
Rahmat Hidayat ◽  
Arnida Lailatul Latifah ◽  
Misnawati
Keyword(s):  
Time Series ◽  
Regional Climate Model ◽  
Bias Correction ◽  
Climate Model ◽  
Regional Climate ◽  
Standardized Precipitation Index ◽  
Weather Data ◽  
Projection Data ◽  
Model Data ◽  
Rcp 8.5

Drought is a natural disaster that occurs slowly and lasts longer until the wet season occurred. Drought occurred in expected time, so that preparations and preparedness can be made in dealing with drought disasters. Therefore, we need an overview of future drought events (or projections).In this study, Standardized Precipitation Index (SPI) was used as drought index. The occurrence of drought is closely related to weather factors and occurs repeatedly. Time-series weather data is needed to know the time-series weather conditions. Problems with data that often occur can be overcome by using numerical climate modeling which is currently widely used. Regional Climate Model (RCM) is a climate model that can be used to build long-term climate data, both time-series and projection data. The results showed RCM model data required bias correction in order to reduce bias in the CORDEX RCM model data. RCM rainfall models before correction were still biased. Thus, bias correction is needed to reduce bias in models data. Time series obtained from SPI baseline data for 2000-2005 in Lampung and West Sumatra provinces showed SPI value which smaller than the projection SPI value in 2021-2030. While SPI time series with RCP 4.5 and 8.5 scenarios showed different results. SPI with RCP 8.5 scenario have more negative value so that drought occurred more often than RCP 4.5. The negative SPI index that often occured in RCP 8.5 scenario appeared to be in RCM IPSL and MPI models year 2025-2030.

scholarly journals Scaling Low Resolution Regional Climate Model Results to High Resolution for Predicting Rice and Maize Production under Climate Change Disaster Scenario

2020 ◽  
Author(s):  
Teerachai Amnuaylojaroen ◽  
Pavinee Chanvichit
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Climate Model ◽  
Crop Yields ◽  
Regional Climate ◽  
Northern Thailand ◽  
Maize Production ◽  
Production Risk ◽  
Disaster Scenario ◽  
Near Future

Climate change effect on human-living in verities of way such as health and food security. This study presents predicting crop yields, and production risk in the near future (2020-2029) in northern Thailand using coupling 1 km resolution of regional climate model which is downscaled using a conservative remapping method and the Decision Support System for the Transfer of Agrotechnology (DSSAT) modeling system. The accuracy of the climate and agricultural model was appropriate compared to the observations with Index of Agreement (IOA) in ranges of 0.65 - 0.89. The DSSAT modeling system predicts that rice, and maize production will decrease by 5% and 4% in northern Thailand. In addition, a short-term risk analysis of rice and maize production has shown that, in the context of climate change, maize production appears to be at a high risk of low production in the near future, while rice cultivation might be a low risk.

scholarly journals Regional Climate Model–Simulated Timing and Character of Seasonal Rains in South America

2007 ◽  
Vol 135 (7) ◽  
pp. 2642-2657 ◽  
Author(s):  
Sara A. Rauscher ◽  
Anji Seth ◽  
Brant Liebmann ◽  
Jian-Hua Qian ◽  
Suzana J. Camargo
Keyword(s):  
South America ◽  
Regional Climate Model ◽  
Rainy Season ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Model ◽  
Northeast Brazil ◽  
Monsoon Region ◽  
Enso Events ◽  
Dry Spells

Abstract The potential of an experimental nested prediction system to improve the simulation of subseasonal rainfall statistics including daily precipitation intensity, rainy season onset and withdrawal, and the frequency and duration of dry spells is evaluated by examining a four-member ensemble of regional climate model simulations performed for the period 1982–2002 over South America. The study employs the International Centre for Theoretical Physics (ICTP) regional climate model, version 3 (RegCM3), driven with the NCEP–NCAR reanalysis and the European Centre–Hamburg GCM, version 4.5. Statistics were examined for five regions: the northern Amazon, southern Amazon, the monsoon region, Northeast Brazil, and southeastern South America. RegCM3 and the GCM are able to replicate the distribution of daily rainfall intensity in most regions. The analysis of the rainy season timing shows the observed onset occurring first over the monsoon region and then spreading northward into the southern Amazon, in contrast to some previous studies. Correlations between the onset and withdrawal date and SSTs reveal a strong relationship between the withdrawal date in the monsoon region and SSTs in the equatorial Pacific, with above-average SSTs associated with late withdrawal. Over Northeast Brazil, the regional model errors are smaller than those shown by the GCM, and the strong interannual variability in the timing of the rainy season is better simulated by RegCM3. However, the regional model displays an early bias in onset and withdrawal over the southern Amazon and the monsoon regions. Both RegCM3 and the GCM tend to underestimate (overestimate) the frequency of shorter (longer) dry spells, although the differences in dry spell frequency during warm and cold ENSO events are well simulated. The results presented here show that there is potential for added value from the regional model in simulating subseasonal statistics; however, improvements in the physical parameterizations are needed for this tropical region.

Qinghai-Xizang (Tibetan) Plateau climate simulation using the regional climate model RegCM3

2013 ◽  
Vol 57 (3) ◽  
pp. 173-186 ◽  
Author(s):  
X Wang ◽  
M Yang ◽  
G Wan ◽  
X Chen ◽  
G Pang
Keyword(s):  
Tibetan Plateau ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Climate Simulation

Evaluation of net shortwave radiation over China with a regional climate model

2020 ◽  
Vol 80 (2) ◽  
pp. 147-163
Author(s):  
X Liu ◽  
Y Kang ◽  
Q Liu ◽  
Z Guo ◽  
Y Chen ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Monsoon Region ◽  
Clear Sky ◽  
Sky Conditions

The regional climate model RegCM version 4.6, developed by the European Centre for Medium-Range Weather Forecasts Reanalysis, was used to simulate the radiation budget over China. Clouds and the Earth’s Radiant Energy System (CERES) satellite data were utilized to evaluate the simulation results based on 4 radiative components: net shortwave (NSW) radiation at the surface of the earth and top of the atmosphere (TOA) under all-sky and clear-sky conditions. The performance of the model for low-value areas of NSW was superior to that for high-value areas. NSW at the surface and TOA under all-sky conditions was significantly underestimated; the spatial distribution of the bias was negative in the north and positive in the south, bounded by 25°N for the annual and seasonal averaged difference maps. Compared with the all-sky condition, the simulation effect under clear-sky conditions was significantly better, which indicates that the cloud fraction is the key factor affecting the accuracy of the simulation. In particular, the bias of the TOA NSW under the clear-sky condition was <±10 W m-2 in the eastern areas. The performance of the model was better over the eastern monsoon region in winter and autumn for surface NSW under clear-sky conditions, which may be related to different levels of air pollution during each season. Among the 3 areas, the regional average biases overall were largest (negative) over the Qinghai-Tibet alpine region and smallest over the eastern monsoon region.

Sign in / Sign up

Export Citation Format

Share Document